Systems and methods for determining signal coverage

ABSTRACT

Methods and systems are provided for processing signal strength information from a radio frequency transmitter and for determining signal coverage for a wireless device. In one embodiment, the method includes receiving signal strength information indicating a power for the radio frequency transmitter at one or more first locations; receiving location information representing a geographic location for one or more second locations; dividing the received signal strength information into one or more subsets of signal strength information; determining, for each of the one or more subsets, a local mean such that the local mean represents an average for one of the one or more subsets; and estimating a location for the local mean based on the received location information.

CROSS REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional PatentApplication No. 60/225,305, entitled “SYSTEM AND METHOD FOR ESTIMATINGRADIO COVERAGE AND PROPAGATION,” filed on Aug. 15, 2000, the disclosureof which is expressly incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

[0002] A. Field of the Invention

[0003] The present invention relates generally to processing signalstrength information received from a radio frequency transmitter. Moreparticularly, the present invention relates to systems and methods forprocessing signal strength information and position information todetermine signal coverage.

[0004] B. Description of the Related Art

[0005] A wireless device, such as a mobile phone, a radio, or atelevision, must be capable of receiving a signal to operateeffectively. In the case of mobile phones, wireless service providersmeasure power for the signal at various locations and then estimatewhether the signal can be received in one or more geographic areas, suchas cells or microcells. The wireless service provider may then adjustthe power of the transmitter of the signal such that the mobile phonescan receive the signal within the one or more geographic areas. Thisprocess helps ensure that the wireless device can receive the signal andthus operate effectively.

[0006] Past approaches to the process of estimating signal strengthwithin a geographic area provided poor estimates. That is, theseestimates varied greatly within an area, forcing the wireless serviceprovider to provide unnecessary extra transmitter power to account forthe variations in the estimates. If a wireless service provider fails toadd extra transmitter power, a user of the mobile phone may be able toreceive the signal in some geographic areas but suffer a serviceinterruption in other geographic areas because the signal may be tooweak. However, increasing power at a transmitter may increase operatingcosts. Accordingly, there is a need for systems and methods fordetermining estimates of signal coverage with less variability,permitting wireless service providers to precisely provide power to anarea.

SUMMARY OF THE INVENTION

[0007] To address one or more limitations of the prior art, there isprovided a method for processing signal strength information from aradio frequency transmitter. The method includes, for example, receivingsignal strength information indicating a power for the radio frequencytransmitter at one or more first locations; receiving locationinformation representing a geographic location for one or more secondlocations; dividing the received signal strength information into one ormore subsets of signal strength information; determining, for each ofthe one or more subsets, a local mean such that the local meanrepresents an average for one of the one or more subsets; and estimatinga location for the local mean based on the received locationinformation.

[0008] In another embodiment, there is provided a method for determininga signal coverage for a wireless device. The method including, forexample, receiving signal strength information for a signal; receivinglocation information representing a geographic location for one or morefirst locations; determining one or more local means based on thereceived signal strength information; estimating one or more secondlocations for the one or more local means based on the one or more firstlocations; transforming the one or more second locations into a route;and calculating the signal coverage for the route based on a signalcoverage for at least one of the one or more second locations.

[0009] In still another embodiment, there is provided a system forprocessing signal strength information from a radio frequencytransmitter. The system including, for example, means for receivingsignal strength information indicating a power for the radio frequencytransmitter at one or more first locations; means for receiving locationinformation representing a geographic location for one or more secondlocations; means for dividing the received signal strength informationinto one or more subsets of signal strength information; means fordetermining, for each of the one or more subsets, a local mean such thatthe local mean represents an average for one of the one or more subsets;and means for estimating a location for the local mean based on thereceived location information.

[0010] Moreover, in another embodiment, there is provided a system fordetermining a signal coverage for a wireless device. The systemincluding, for example, means for receiving signal strength informationfor a signal; means for receiving location information representing ageographic location for one or more first locations; means fordetermining one or more local means based on the received signalstrength information; means for estimating one or more second locationsfor the one or more local means based on the one or more firstlocations; means for transforming the one or more second locations intoa route; and means for calculating the signal coverage for the routebased on a signal coverage for at least one of the one or more secondlocations.

[0011] Furthermore, in an embodiment, there is provided a system forprocessing signal strength information from a radio frequencytransmitter. The system including, for example, at least one memoryincluding, for example, code that receives signal strength informationindicating a power for the radio frequency transmitter at one or morefirst locations, code that receives location information representing ageographic location for one or more second locations, code that dividesthe received signal strength information into one or more subsets ofsignal strength information, and code that determines, for each of theone or more subsets, a local mean such that the local mean represents anaverage for one of the one or more subsets; and at least one processorthat executes the code.

[0012] In still another embodiment, there is provided a system fordetermining a signal coverage for a wireless device. The systemincluding, for example, at least one memory including, for example, codethat receives signal strength information for a signal, code thatreceives location information representing a geographic location for oneor more first locations, code that determines one or more local meansbased on the received signal strength information, code that estimatesone or more second locations for the one or more local means based onthe one or more first locations, code that transforms the one or moresecond locations into a route, and code that calculates the signalcoverage for the route based on a signal coverage for at least one ofthe one or more second locations; and at least one processor thatexecutes the code.

[0013] It is to be understood that both the foregoing generaldescription and the following detailed description are exemplary andexplanatory only and are not restrictive of the invention, as described.Further features and/or variations may be provided in addition to thoseset forth herein. For example, the present invention may be directed tovarious combinations and subcombinations of the disclosed featuresand/or combinations and subcombinations of several further featuresdisclosed below in the detailed description.

DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which are incorporated in andconstitute a part of this specification, illustrate embodiments of theinvention and, together with the description, explain the advantages andprinciples of the invention. In the drawings,

[0015]FIG. 1 illustrates a system block diagram for processing signalstrength information and position information, consistent with themethods and systems of the present invention;

[0016]FIG. 2 illustrates a high-level flowchart of a method fordetermining the signal coverage of a radio frequency transmitter,consistent with the methods and systems of the present invention;

[0017]FIG. 3 illustrates an exemplary flowchart for collectinginformation, in accordance with methods and systems consistent with thepresent invention;

[0018]FIG. 4 illustrates an exemplary flowchart for processing collectedinformation, in accordance with methods and systems consistent with thepresent invention;

[0019]FIG. 5A illustrates a table of collected information, inaccordance with methods and systems consistent with the presentinvention;

[0020]FIG. 5B illustrates an exemplary signal trace, in accordance withmethods and systems consistent with the present invention;

[0021]FIG. 5C illustrates collecting information, in accordance withmethods and systems consistent with the present invention;

[0022]FIG. 6 illustrates a table of information processed, in accordancewith methods and systems consistent with the present invention;

[0023]FIG. 7A illustrates an exemplary flowchart for determining astatistic, in accordance with methods and systems consistent with thepresent invention;

[0024]FIG. 7B illustrates another table of information processed, inaccordance with methods and systems consistent with the presentinvention;

[0025]FIG. 7C illustrates a histogram of difference values determined inaccordance with methods and systems consistent with the presentinvention;

[0026]FIG. 8 illustrates an exemplary flow chart for determining thesignal coverage for a wireless device along a route, in accordance withmethods and systems consistent with the present invention; and

[0027]FIG. 9 illustrates a route, in accordance with methods and systemsconsistent with the present invention.

DETAILED DESCRIPTION

[0028] Reference will now be made in detail to the exemplary embodimentsof the invention, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

[0029] In accordance with an embodiment of the present invention, a userof the system may collect a signal from a radio frequency transmitterand measure signal strength for the received signal. The system may alsocollect the signal from various locations, such as over an area or overa route. For example, the user of the system may drive along a highway,measuring received signal strength information at various points alongthe highway. While measuring the received signal strength information,the system may also record the location of the system with a globalpositioning system receiver.

[0030] When the user of the system completes data collection, the systemmay preprocess the received signal strength information and positioninformation. The preprocessed information may then be further processedto determine a statistic, such as a standard deviation based on thereceived signal strength information. The system may use the processedinformation to then determine an indication of signal coverage at one ormore geographic locations. In one embodiment, the indications of signalstrength may be based on the standard deviation. The system may use thestandard deviation to provide an indication of signal coverage thatreduces the effects of terrain and that includes the effects ofvariations from obstructions on the terrain (e.g., man made or naturalstructures including trees, building, bridges, and etc.). Moreover, theindication of signal strength may be provided to a user, such as awireless service provider, in the form of signal coverage information,enabling the user to determine whether one or more wireless devices (orreceivers) may receive the signal from the radio frequency transmitter.

[0031] Signal coverage information may provide an indication of thecoverage of a signal—i.e., whether a signal may be detected and/orprocessed by one or more wireless devices, such as a radio, atelevision, or a mobile phone. Signal coverage information may indicate,for example, one or more of the following: signal coverage for an area,signal coverage for a route, signal coverage at a location, maximumduration of a service fade, and maximum length of a service fade.Accordingly, in one embodiment, the system may provide a user, such as awireless service provider, an indication of whether one or more wirelessdevices may detect and/or process a signal from a radio frequencytransmitter at one or more geographic locations. For example, the systemmay permit a wireless service provider to determine whether the serviceprovider provides adequate coverage to wireless devices within an areaor route.

[0032]FIG. 1 shows an exemplary system for determining the signalcoverage of a radio frequency transmitter. Referring to FIG. 1, thesystem 100 includes an antenna 105, a receiver 120, a global positioningsystem (GPS) receiver 130, a processor 140, a storage module 150, aninput module 110, and an output module 160.

[0033] The receiver 120 may include a spectrum analyzer or any otherdevice(s) capable of receiving electromagnetic energy and determiningthe signal strength of a radio transmitter, such as radio transmitter180 and its corresponding antenna 185.

[0034] The GPS receiver may include a standard GPS receiver, forexample, a differential GPS receiver, or any other device(s) capable ofproviding position information including one or more of the following: alatitude, a longitude, a time, a heading, and/or a velocity.

[0035] Although FIG. 1 illustrates only a single processor 140, thesystem 100 may alternatively include a set of processors. The processor140 may also include, for example, one or more of the following: one ormore central processing units, a co-processor, memory, registers, andother data processing devices and systems as appropriate. Moreover, theprocessor 140 may control the receiver 120 and/or GPS receiver 130;collect and then store information provided by the receiver 120 and/orGPS receiver 130; preprocess and/or process the collected information;estimate a statistic, such as standard deviation, based on the collectedinformation; and determine the signal coverage of a radio frequencytransmitter.

[0036] In one embodiment, the system 100 may be mobile and placed in amotor vehicle, permitting collection of signal strength information andposition information over a coverage area or a route. In thisembodiment, a second processor (not shown) may also be used to processthe collected information from the mobile system 100, estimate thestatistic, and then determine the signal coverage of the radio frequencytransmitter.

[0037] The input module 110 may be implemented with a variety of devicesto receive a user's input and/or provide the input to the processor 140.Some of these devices (not shown) may include, for example, a networkinterface card, a modem, a keyboard, a mouse, and an input storagedevice.

[0038] The storage module 150 may be embodied with a variety ofcomponents or subsystems including, for example, a hard drive, anoptical drive, a general-purpose storage device, a removable storagedevice, and/or other devices capable of storing. Further, althoughstorage module 150 is illustrated in FIG. 1 as being separate orindependent from processor 140, the storage module 150 and processor 140may be implemented as part of a single platform or system.

[0039] The radio frequency transmitter 180 and antenna 185 may include,for example, a cellular site transmitter, a satellite transmitter, abroadcast transmitter (e.g., AM or FM transmitter), a wirelessnetworking transmitter, and any other transmitter of electromagneticenergy.

[0040]FIG. 2 shows an exemplary flow chart for determining signalcoverage of a radio frequency transmitter. Referring to FIG. 2, a system100 may begin (step 200) by collecting information (step 210) within anarea or over a route. The collected information may include signalstrength information for a radio frequency transmitter 180 and location(or position) information of the system 100. When collection within thearea or over a route is complete, the system 100 may preprocess thecollected information (step 220); perform processing, such asstatistical processing, (step 230) to estimate a statistic thatrepresents the variations in signal strength, such as variations due to“shadow fading” (i.e., fading from obstruction on the terrain, such asnatural and man-made structures); and determine the signal coverage ofthe radio frequency transmitter (step 240) by providing an indication ofreceived signal strength for the radio frequency transmitter, such as asignal coverage percentage for an area or for a route, a percentage (orvalue) indicating signal coverage at a location, a duration of a servicefade, and/or a length of a service fade.

[0041]FIG. 3 illustrates the steps associated with collecting dataconsistent with the methods and systems of the present invention.Referring to FIG. 3, the system 100 may perform data collection (see,e.g., step 210 at FIG. 2) from a motor vehicle and may collect data atvarious geographic locations while moving within an area or over a route(step 310). In one embodiment, the processor 140 may receive positioninformation (also referred to hereinafter as geolocation data) from aGPS receiver 130 (step 320). The position information may include, forexample, one or more of the following: latitude, longitude, heading,velocity, and time according to GPS (referred to hereinafter as GPStime). The GPS receiver 130 may provide the processor 140 with theposition information at various times or at a periodic interval, such asonce every second.

[0042] The receiver 130 may receive a signal from a transmitter, such astransmitter 180 and antenna 185, and measure the received signalstrength associated with the signal. The processor 140 may then receivethe measured signal strength information from the receiver 120 (step330).

[0043] In one embodiment, the receiver 120 includes a spectrum analyzer(not shown) that measures the received signal strength of the signal. Inthis embodiment, the received signal strength of the signal may bemeasured as power and may be of the form of the following equation:$\begin{matrix}{{P_{r} = {P_{0} \cdot \left( \frac{R_{0}}{R} \right)^{\gamma} \cdot \kappa}};{R \geq R_{0}}} & {{Equation}\quad (1)}\end{matrix}$

[0044] where R represents a first distance from the radio transmitter tothe receiver, such as distance in the 1 to 20 kilometer range; R₀represents a second distance from the radio transmitter to the receiver;P_(r) represents the received power (in milliwatts) at distance R(kilometers) from the radio transmitter; P₀ represents the powerreceived at distance R₀ (kilometers) from the radio transmitter; γrepresents path loss in the given mobile radio environment (usuallyreferred to as the propagation exponent); and κ is a variable correctionfactor based on the transmitter or receiver. The book titled “Antennasand Propagation for Wireless Communication Systems,” Simon R. Saunders,John Willey & Sons, 1999, describes, inter alia, received power and isincorporated herein by reference in its entirety.

[0045] The processor 140 may continue collecting (step 340) the receivedsignal strength information and position information until sufficientinformation from various geographic locations are collected. Forexample, the system 100 may be installed in a vehicle that drives over ahighway. As the system 100 moves along the highway, the processor 140may receive received signal strength information corresponding to atransmitter (e.g., transmitter 180) and receive position information forthe system 100 (i.e., the location of the system 100 on the highway).When the system 100 completes collecting information at various pointsalong the route, the system 100 may stop collecting (No at step 340) andform a file including the received signal strength information andposition information (step 350). This file formed by the processor 140is referred to hereinafter as a spectrum and geolocation data (SGD)file.

[0046] The processor 140 may store, in the storage module 150, the SGDfile including one or more position velocity (PV) records, received fromthe GPS receiver 130, and one or more trace (TR) records, received fromthe receiver 120. The PV record may include, for example, at least oneor more of the following: PC time, GPS time, latitude, longitude,velocity, and heading. The TR record may include, for example, at leastone or more of the following: PC time, trace (TR) type (e.g., whetherthe signal trace includes signal samples versus time or signal samplesversus frequency), and signal samples. In one embodiment, the processor140 may receive position information from the GPS receiver 130 and alsoindependently receive signal strength information from the receiver 120.The processor 140 may complete data collection (step 360) by storing theSGD file.

[0047]FIG. 4 illustrates exemplary steps associated with preprocessingan SGD file. To preprocess the SGD file, the processor 140 may perform,for example, one or more of the following: apply a time smoothingalgorithm to the SGD file to adjust the PC time to GPS time (step 420)in the PV records; sort the SGD file in ascending order based on PC time(step 430); divide each TR record into one or more subsets based on thevelocity of the receiver 120 (step 440); calculate a local mean for eachof the subsets (step 450); estimate a geolocation for each of the localmeans (step 460); interpolate, if necessary, a local mean based on thevelocity of the receiver 120 (step 470); perform data reduction (step480); and reject information from interfering signals (step 490).

[0048] The SGD file may include, for example, two types of time fields.The first time field is PC time and is based on the internal timingsystem of the processor 140. The processor 140 may utilize PC time whenstoring a PV record or a TR record. The second time field corresponds toGPS time and is based on time according to the GPS system. The GPS timemay thus indicate the time when the geolocation was made by the GPSreceiver 130. Accordingly, when the processor 140 stores a TR or PVrecord, the processor 140 records a PC time with the record. But when aPV record is stored, the record includes a GPS time and a PC time.

[0049] In one embodiment, the system 100 may adjust the one or more PCtime values of the PV records into a linear relationship that is definedby the slope and intercept of the one or more GPS time values in the SGDfile. This fitting may serve to smooth the one or more PC time values.The PC time values after being smoothed may conform to the followingequation:

PCtime*=m×GPStime+n  Equation (2)

[0050] where PCtime* represents the PCtime of each PV record in the SGDfile after time smoothing; m represents the slope of the GPS times inthe SGD file; and n represents the intercept of the GPS times in the SGDfile.

[0051] In one embodiment, the slope, m, and the intercept, n, isdetermined by the following equations: $\begin{matrix}{m = \frac{{N \cdot {\sum\limits_{k}{x_{k}y_{k}}}} - {\sum\limits_{k}{x_{k} \cdot {\sum\limits_{k}y_{k}}}}}{{N \cdot {\sum\limits_{k}x_{k}^{2}}} - \left( {\sum\limits_{k}x_{k}} \right)^{2}}} & {{Equation}\quad (5)} \\{n = \frac{{\sum\limits_{k}{y_{k} \cdot {\sum\limits_{k}x_{k}^{2}}}} - {\sum\limits_{k}{x_{k} \cdot {\sum\limits_{k}{x_{k}y_{k}}}}}}{{N \cdot {\sum\limits_{k}x_{k}^{2}}} - \left( {\sum\limits_{k}x_{k}} \right)^{2}}} & {{Equation}\quad (6)}\end{matrix}$

[0052] where y represents one or more PC time values; x represents oneor more GPS time values; and k varies from 1 to N and represents thek_(th) PV record of an SGD file containing N records.

[0053] To sort the SGD file in ascending order based on time (step 430),the processor 140 may sort the PV and TR records in the SGD file basedon PC time values. For example, the processor 140 may sort the PV and TRrecords in ascending or descending order.

[0054]FIG. 5A shows an exemplary table of PV and TR records after theprocessor 140 performs time smoothing (step 420) and sorting (step 430).Referring to FIG. 5A, the first record is a PV record including a PCtime of “60449.56,” a latitude of “40.77072,” a longitude of “−74.0281,”a velocity of “38” miles per hour, and a GPS time of “297” seconds. Thesecond record is a TR record corresponding to the spectrum (i.e.,received signal strength over time) of a signal, such as the signal fromtransmitter 180. The TR record includes a PC Time of “60450.39,” a tracetype (TR type) of “2” to indicate that the signal trace corresponds tosignal samples over an interval of time, and received signal strengthvalues (i.e., the signal samples) of −“115.93,” “−113.87,” “−116.0,”“−120.0,” “−121.0,” and “−121.1.” Although this record only shows sixreceived signal strength values, a skilled artisan may recognize thatadditional received signal strength values may also be stored with theTR record. Moreover, the received signal strength values may be based ona signal trace representing the samples of the signal at one or moretime instants or frequencies.

[0055]FIG. 5B shows an exemplary signal trace from receiver 120 withreceived signal sample values measured at one or more times. Thereceived signal strength values for each TR record represents themeasured samples at one or more times. The processor 140 may store thesignal trace in the TR record as received signal strength information,as shown in FIG. 5A. Alternatively, a skilled artisan may recognize thatthe signal trace may instead represent samples of the signal measured atone or more frequencies.

[0056] When the records of the SGD file have been time smoothed andsorted, the processor 140 may then divide each trace of the TR recordinto one or more subsets based on the velocity of the receiver 120 (step440). In one embodiment, the processor 140 may determine the distancecovered by the receiver 120 based on the receiver velocity. Theprocessor 140 may then divide each trace into one or more subsets suchthat no subset is larger than a distance, such as 40 times thewavelength of the transmitter. For example, a transmitter at 1.2 GHz mayhave a wavelength of 0.25 meters. In this example, each trace may bedivided into one or more subsets such that each of the subsets would beless than or equal to 10 meters (i.e., 40 times the wavelength of 0.25meters). Although 10 meters is used as the distance, any other distancemay be used instead.

[0057]FIG. 5C illustrates the system 100 collecting data from the radiotransmitter 180 at various geographic locations between the route from A510 to B 595. The stars 521-525 represent when the system 100 receivesgeolocation information from the GPS receiver (not shown). The signaltraces 531-534 represent received signal strength information (see,e.g., FIG. 5B) collected over a 1-second interval. Since the system 100varies its speed while traveling from point A 510 to point B 595, thesignal traces 531-534 correspond to different distances. That is, a1-second signal trace collected while traveling at 60 miles per hourrepresents 26.8 meters. On the other hand, a 1-second signal tracecollected while traveling at 30 miles per hour represents 13.4 meters.To limit the maximum distance associated with any one signal trace, theprocessor 140 may divide the signal trace (i.e., the received signalstrength information) within each TR record into one or more subsetsbased on the velocity of the receiver 120 (step 440).

[0058] Referring again to FIG. 5B, the sample represents a distance ofless than 10 meters and may thus be divided into a single subset,forming a single TR record with received signal strength informationincluding “−115.93, ”“−113.87,” “−116,” “−120,” “−121,” and “−121.1,” asshown in FIG. 5A. Although this example includes a single subset, a TRrecord may alternatively be divided a plurality of subsets.

[0059] To calculate a local mean for each of the subsets (step 450), theprocessor 140 may average the received signal strength information witheach subset. In one embodiment, the first TR record of FIG. 5A may bedivided into a single subset and the received signal strength values forthe subset may be averaged. In this example, the local mean for thefirst TR record of FIG. 5A is the average of “−115.93,” “−113.87,”“−116,” “−120,” “−121,” and “−121.1” (or “−117.08 dBm, averaged in thelinear domain). The processor 140 may repeat determining the local meanfor all of the TR records and the corresponding subset(s) in the SGDfile.

[0060] To estimate a position for each of the local means (step 460),the processor 140 may associate a location (or geolocation) with eachlocal mean determined in step 450. The processor 140 may estimate alocation for a local mean based on the PV record preceding and the PVrecord following the local mean. For example, referring to FIG. 5A, thefirst TR record is preceded by a PV record taken at “60449.56” and isfollowed by a PV record at “60451.56.”

[0061] To determine a geolocation for a local mean, the followingequation may be used: $\begin{matrix}{{{Lg}\left( \tau_{k} \right)} = {{\frac{{Lg}_{2} - {Lg}_{1}}{t_{2} - t_{1}}\left( {\tau_{k} - t_{1}} \right)} + {Lg}_{1}}} & {{Equation}\quad (5)} \\{{{Lt}\left( \tau_{k} \right)} = {{\frac{{Lt}_{2} - {Lt}_{1}}{t_{2} - t_{1}}\left( {\tau_{k} - t_{1}} \right)} + {Lt}_{1}}} & {{Equation}\quad (6)}\end{matrix}$

[0062] where Lg₁, Lt₁, t₁ represent the longitude, latitude, and time,respectively, for the PV record preceding the TR record for the subsetfor which the position is being estimated; Lg₂, Lt₂, t₂ represent thelongitude, latitude, and time, respectively, for the PV record after thesubset for which the position is being estimated; and τ_(k) is a timeassociated with the k^(th) local mean (e.g., the time associated withthe k^(th) subset of the given TR record). The processor 140 may useEquations 5 and 6 for each TR record and its corresponding subsets inthe SGD file.

[0063] The processor 140 may interpolate a local mean when the distanceexceeds a predetermined distance (step 470). The processor 140 maydetermine the distance between two consecutive local means usinglocation information for each of the consecutive local means. When thedistance exceeds the predetermined threshold, the processor 140 may usetwo consecutive local means to interpolate a new local mean and acorresponding location. In one embodiment, the processor 140 may use apredetermined threshold of a distance corresponding to the averagevelocity multiplied by the average time between TR records, where theaverage velocity may be calculated based on the PV records. For example,when the distance between two consecutive local means exceeds thepredetermined threshold, the processor 140 may average the twoconsecutive local means and corresponding locations. The processor 140may then use the average local mean and average location information asan interpolated local mean. The processor 140 may also insert theinterpolated local mean into the SGD file. In one embodiment, theprocessor 140 may not perform step 470 when the time difference betweenconsecutive PV records exceeds 2 seconds.

[0064]FIG. 6 shows the SGD file of FIG. 5A after estimating the locationfor each subset (step 460) and interpolating (step 470). In oneembodiment, after performing steps 460 and 470, the processor 140 maycreate a second file, referred to herein after as an m-file, as shown inthe exemplary table of FIG. 6. The fields in the m-file of FIG. 6include longitude (Long), latitude (Lat), local mean, velocity ofreceiver (v), LaGrange Interpolation (Lagr-lntp), average, anddifference. For example, the local mean “−113.8” includes a longitude of“−74.0283,” a latitude of “40.77081,” a velocity of “39.14” mph, aLagr-lntp value of “0.” Moreover, the record with a Lagr-lntp value of“1” is a record that is interpolated. The processor 140 may use theaverage and difference fields to determine one or more statistics, asdescribed in additional detail below.

[0065] The processor 140 may also perform data reduction on the m-file(step 480) to remove redundant values for the same location. Forexample, if the system 100 collects data while in a stationary position(e.g., while stopped at a red light), the SGD file or the m-file mayinclude one or more local means for the same location. The processor 140may thus average the repeated local means and location information intoa single local mean at that location. Alternatively, the processor 140may delete the repeated local means and location information to removethe redundant values.

[0066] To reject interfering signals (step 49), the processor 140 mayalso monitor the frequency. For example, when the receiver 120 measuresthe received signal strength of a signal of interest (e.g., thefrequency of the transmitter 180), the processor 140 may store instorage module 150 the received signal strength for the signal ofinterest and discard signal strength measurements that do not correspondto the frequency of the signal of interest, such as measurements from aninterfering signal.

[0067]FIG. 7A shows exemplary steps for statistically processing a file,such as the m-file, to determine a statistic, such as a standarddeviation. The processor 140 may read the local mean from the SGD fileof FIG. 6 (step 720); calculate an average over a window (step 730); anddetermine a difference between the local mean and the window average(step 740). The processor 140 may also determine whether additionallocal means need processing (step 750). If so (yes at step 750), theprocessor 140 may slide the window (step 755) and repeat steps 720-750for another local mean. When additional local means do not needprocessing (no at step 750), the processor 140 may estimate a standarddeviation (σ) from all the differences calculated in step 740. Althougha standard deviation is used, a skilled artisan may recognize that anyother statistic may be used instead, such as a variance, or higher ordermoment.

[0068] To read the local mean from the m-file (step 720), the processor140 may read the m-file stored in the storage module 150. For example,processor 140 may read the first record associated with the first localmean, such as the values from the first record of FIG. 6 (see, e.g.,record number 1 of FIG. 6).

[0069] To calculate an average over a window (step 730), the processor140 may compute the average over a predetermined window. FIG. 7B showsFIG. 6, with the window average stored in the first record of the window(i.e., record 1). Referring to FIG. 7B, the predetermined window (see,e.g., the first window 790 of FIG. 7B) may include a window size of 2records. With a window size of 2 records, the processor 140 may computea window average by averaging the local means for the first and secondrecords of FIG. 7B. The processor 140 may then associate the windowaverage with the first record in the window (e.g., record 1). In thisexample, the processor 140 may assign the window average of −113.4 dBmto record number 1.

[0070] On the other hand, in one embodiment, the processor 140 maycalculate an average over a predetermined window that includes an oddnumber of records, such as five records. With a window size of fiverecords, the processor 140 computes a window average by averaging thelocal means for five of the records of FIG. 7B. For example, theprocessor 140 may determine the window average for records 1-5 and thenassociate the window average to the middle record (i.e., record 3). Inthis example, the processor 140 may assign the window average of −112.02(i.e., the average of −113.8, −113.06, −111.58, −110.78, and −111.6) torecord number 3. The processor 140 may then slide the window to includerecords 2-6. In one embodiment, the window average may be a Gaussianwindow (also referred to as a normal window) that calculates a weightedaverage across the Gaussian window (e.g., five records) such that thedetermined window average is associated with the center record of thewindow.

[0071] A skilled artisan may recognize that other window sizes may beused instead. By way of example, the window size may be selected basedon the frequency (or wavelength) of the signal received by receiver 120.In one embodiment, the window size may correspond to a 25 meter windowat 500 MHz band, a 40 meter window at frequencies within the very highfrequency (VHF) range, and a 20 meter window at frequencies within ultrahigh frequency (UHF) range of the electromagnetic spectrum. In oneembodiment, a large window size may include terrain contributions thatimpact the local means (e.g., increasing the standard deviation of thelocal mean). For example, with a window size of 25 meters, the windowaverage (step 730) would include the average of the local mean of thefirst record with any other record that is within a distance of 25meters from the first record. The articles titled “Propagation at 500MHz for mobile radio,” Davis et al., IEE Proc. 132, Pt.F, No. 8, 1985,and “Signal strength prediction in urban areas,” Parsons et al., IEEProc., 130, Pt.F, No.5, 1983, describe inter alia, window sizes and areboth incorporated herein by reference in its entirety.

[0072] To determine a difference between a local mean and a windowaverage (step 740), the processor 140 may subtract the window averagefrom the local mean. Referring again to FIG. 7B, this difference may bestored in the column labeled “Difference.”

[0073]FIG. 7C shows a histogram of the difference values determined instep 740 (see, e.g., “Difference” values of FIG. 7B). When the processor140 uses a window size that yields a lognormal distribution, as shown inFIG. 7C, the processor 140 may be using the correct window size. In oneembodiment, the processor 140 may vary the window size until adistribution approximating that of a lognormal distribution is realized.Moreover, the lognormal distribution of FIG. 7C may suggest that thedifference values correspond to shadow fading, such as fading producedby obstructions on the terrain, rather than slow fading, such as fadingproduced by slow variations in the terrain.

[0074] To determine whether additional local means need processing (step750), the processor 140 may determine whether additional records includelocal means without a corresponding window average and difference. Ifso, the processor 140 slides the window (step 755) by moving (orsliding) the window over by one record. Referring again to FIG. 7B, witha window distance of two records, the window would slide from the firstwindow 790 to the second window 795, which includes records 2 and 3.

[0075] The processor 140 may then repeat steps 720-750 by, for example,reading the local mean of −113.06 (step 720) from record 2 (see FIG.7B); calculating a window average over the second window, resulting in anew window average of −112.2 (i.e., the linear average of −113.06 and−111.58) (step 730); computing a difference of 1.06 (step 740); anddetermining whether additional local means remain to be processed (step750).

[0076] When the processor 140 computes all of the differences based onthe local means and window average, the processor 140 may use all of thedifference values to compute a statistic, such as a standard deviation(σ) (step 760). The standard deviation of all the difference values maybe computed according to the following equation: $\begin{matrix}{\sigma = \sqrt{\frac{{n{\sum x_{i}^{2}}} - \left( {\sum x_{i}^{2}} \right)}{n\left( {n - 1} \right)}}} & {{Equation}\quad (7)}\end{matrix}$

[0077] where n is the number of records in the m-file (e.g., 7 in FIG.7B); and x_(i) represents the i^(th) difference value; and i varies from1 to n.

[0078]FIG. 8 illustrates the steps associated with determining signalcoverage, consistent with the systems and methods of the presentinvention. Referring to FIG. 8, a processor 140 may start the stepsassociated with determining signal coverage (step 810) when theprocessor receives a statistic, such as the standard deviation,describing the received signal strength information (see, e.g., step 760of FIG. 7A). The processor 140 may then use an m file and transform thelocation information in the m-file into a route (step 820); initiateroute breaks when the distance between adjacent records is too long(step 830); and calculate signal coverage over the route (step 840) orsub-routes, providing an indication of signal strength along the routeor sub-route.

[0079] To transform the m-file into a route (step 820), the processor140 may transform each local mean and corresponding locationinformation, such as latitude, longitude, velocity, and heading, into aroute with relative distance, direction, and velocity.

[0080] In one embodiment, the position information for each recordwithin the m-file is represented as a position vector. For example, thek^(th) record in an m-file may include the k^(th) position vectordescribing a geographic location. The k^(th) position vector, S(k), maycorrespond to the following equation:

[0081] S(k)=[Longitude(k), Latitude(k), velocity(k), heading(k), LM(k)]Equation (8) where S(k) represents the k^(th) position vector;Longitude(k) represents the longitude value of the k^(th) positionvector; Latitude(k) represents the latitude value of the k^(th) positionvector; velocity(k) represents the velocity of a receiver (e.g.,receiver 120 or GPS receiver 130) for the k^(th) record; heading(k)represents the heading of the receiver for the k^(th) record; and LM(k)represents the local mean of the k^(th) record.

[0082] The vector S(k) is transformed to a new vector, D(k),representing a route. The route, D(k), may be consistent with thefollowing equation:

D(k)=[Δ(k), velocity(k), heading(k), LM(k)]  Equation (9)

[0083] where the latitude and longitude information of S(k) is replacedwith relative distance Δ(k) from the previous record, such as distancein feet from the previous record.

[0084]FIG. 9 shows an exemplary route for records K⁰-K³. Referring toFIG. 9, the route segment between K¹ and K² 910 includes a distance of20 feet (ΔK²), a heading of 90 degrees, a velocity of 40 miles per hour,and a local mean of −115 dBm.

[0085] To initiate a route break, the processor 140 may determinewhether a route segment, such as route segment ΔK¹ and ΔK² of FIG. 9,exceeds a predetermined route segment distance (referred to hereinafteras a break distance). When the route segment exceeds the break distance,the processor 140 may divide the route into two sub-routes. Theprocessor 140 may then determine coverage for each of the sub-routes. Todetermine whether a route break is required, the processor 140 mayevaluate the distances, such as ΔK¹ and ΔK², between points along aroute. For example, if the distance between locations K¹ and K² exceedsthe break distance, the processor 140 may divide the route intosub-routes.

[0086] In one embodiment, the predetermined route break distance isselected such that it is smaller than the distance required to determinethe duration of a service fade. The duration of a service fade is theamount of time a wireless device (or receiver) fails to detect orprocess a signal because the signal is less than the minimum powerrequired by the receiver. The amount of time also corresponds to adistance, such as the distance traveled by the receiver during theservice fade or the distance associate with a TR record. For example, todetect a service fade of a short duration, such as 30 seconds, theprocessor 140 may require a relatively short route segment distance,such as 1000 feet. On the other hand, to detect a longer service fade,of 2 minutes, the route segment distance may also be longer, such as4000 feet.

[0087] With the route break, the processor 140 may compute the signalcoverage, such as signal coverage percentage and duration of a fade,along the first sub-route (e.g., K⁰ to K¹) and the second sub-route (K²to K³), wherein ΔK² may be used as a break in the route. The coveragealong the route, R_(cp), may be determined as a weighted sum of signalcoverage percentages for the route segments (or sub-routes),Cp({overscore (k)}), wherein the weighted sum is normalized by the routelength. R_(cp) may correspond to a single value characterizing thesignal coverage percentage along the entire route. The route coverage,R_(cp), may be computed with the following equation: $\begin{matrix}{R_{cp} = \frac{\sum\limits_{k}{{{C_{p}(k)} \cdot \Delta}\quad (k)}}{\sum\limits_{k}{\Delta \quad (k)}}} & {{Equation}\quad (10)}\end{matrix}$

[0088] where C_(p)(k) is the signal coverage percentage at a point(e.g., points K₀, K₁, K₂, and K₃ of FIG. 9) along the route; and Δ(k) isthe relative distance from a preceding point.

[0089] For each location {overscore (k)} along a route, the processor140 may calculate a signal coverage percentage based on the local meanfor the k^(th) location along the route, the standard deviation (see,e.g., step 760 at FIG. 7), and a service threshold (w_(t)) for awireless device (or receiver) of interest.

[0090] The service threshold (w_(t)) may represent the smallest signalstrength required by a wireless device (or receiver) to detect andprocess a received signal. For example, a wireless device, such as acell phone, may have a service threshold of −80 dBm. To determine thesignal coverage percentage for the cell phone, the processor 140 may seta service threshold of −80 dBm. A local mean (see, e.g., FIG. 6) belowthe service threshold of −80 dBm represents a service fade. That is, thewireless devise, such as a cell phone, may not be able to detect and/orprocess a signal weaker than −80 dBm, resulting in an interruption (orfade) in reception. When a route includes multiple local means atvarious locations along the route, some of the local means may be weakerthan the service threshold, representing a service fade. If consecutivelocal means are weaker than the service threshold, the service fade hasa duration corresponding to the time or distance associated with theconsecutive local means.

[0091] A skilled artisan may also recognize that the signal coveragepercentage for additional wireless devices with different servicethresholds (e.g., −100 dBm) may also be determined by using a differentservice threshold. Accordingly, the system may enable a wireless serviceprovider to determine signal coverage for one or more wireless devicesover an area or route.

[0092] The coverage percentage, Cp({overscore (k)}), may be representedby the following equation: $\begin{matrix}{{{Cp}(r)} = {{{Prob}\left\{ {w \geq w_{t}} \right\}} = {\frac{1}{2} - {{erf}w_{t}} - \frac{{LM}(r)}{\sigma_{LM}}}}} & {{Equation}\quad (11)}\end{matrix}$

[0093] where r represents distance; σ_(LM) represents the standarddeviation (see, e.g., FIG. 7A at step 760); LM(r) represents the localmean at distance r along a route; and erf is a normal distribution errorfunction of the following form: $\begin{matrix}{{{erf}(x)} = {\int_{0}^{y}{\frac{1}{\sqrt{2\pi}}e^{\frac{x^{2}}{2}}\quad {{x}.}}}} & {{Equation}\quad (12)}\end{matrix}$

[0094] Although the standard deviation is used, one of ordinary skillwill recognize that determining signal coverage along a route may beutilized without using the standard deviation determined in step 760 ofFIG. 7A.

[0095] In one embodiment, the system 100 may collect informationincluding signal strength from a radio frequency transmitter 180 andlocation (or position) information for the system 100. When collectionof an area or route is complete, the system 100 may preprocess thecollected information; and perform processing, such as statisticalprocessing, (step 230) to estimate a statistic, such as a standarddeviation, representing “shadow fading” (i.e., fading from natural andman-made structures on the surface of the earth that obstruct thereception of the receiver 120).

[0096] In one embodiment, by using the standard deviation of thedifferences (see, e.g., FIG. 7A at step 740) between each local mean andthe window average, the system 100 may reduce the contribution ofterrain when determining signal coverage over a route or area. Thecontributions from terrain are also referred to as slow fading.Moreover, by reducing the contributions of terrain, the system 100 mayprimarily include contributions from shadow fading (i.e., variations inthe signal strength from man-made or natural structures on the terrain)in the determination of signal coverage.

[0097] A wireless service provider using the system 100 may require lesssignal strength to service a route or an area since the variations basedon terrain have been reduced, or eliminated, from signal coveragedetermination. On the other hand, a service provider not using thesystem 100 may need to provide additional signal power to account forsignal variations associated with terrain along the route.

[0098] By way of example, when the signal coverage percentage isdetermined without reducing the contribution from terrain, the signalcoverage percentage may correspond to a signal coverage percentage of90% for the route. When the contributions from terrain are reduced oreliminated, the system 100 may provide a signal coverage percentage of,for example, 98%. Accordingly, the present invention may provide anindication of signal coverage over an area or route. Moreover, theindication of signal coverage may also provide received signal strengthindications of an area or route with less variation than past approachesby reducing the influence of terrain on such indications by estimatingthe contribution due to shadow fading.

[0099] In one embodiment, the processor provides signal coverageinformation that includes the number of fades with the correspondingduration for all of the fades over a route of a given distance. Forexample, the processor may provide the user with signal coverageinformation indicating that for a 15 mile route, 5 fades occurred withan aggregate duration of 5 minutes. In another embodiment, the processorsimply provides a coverage percentage for the entire route usingequation 9 above. For example, the processor may output to the user acoverage percentage of 99% over a 15 mile route. The processor 140 mayalso provide the signal coverage percentage over each segment of theroute.

[0100] Moreover, in one embodiment, the system 100 may provide fieldstrength data and statistical processing, enabling high-resolution andaccurate signal coverage determination at a location and/or along aroute. Furthermore, the resolution and accuracy may be utilized inenvironments with small cells, where location resolution is a concern.For example, the system 100 may enhance ray-tracing prediction toolsthat locate service fades in environments with small cells, such asmicrocells. In addition, the system may allow derivation of receivedenvelope statistics, such as a probability density function, averageduration of fades, and level crossing rates.

[0101] The above embodiments and other aspects and principles of thepresent invention may be implemented in various environments. Suchenvironments and related applications may be specially constructed forperforming the various processes and operations of the invention or theymay include a general-purpose computer or computing platform selectivelyactivated or reconfigured by program code (also referred to as code) toprovide the necessary functionality. The processes disclosed herein arenot inherently related to any particular computer or other apparatus,and may be implemented by a suitable combination of hardware, software,and/or firmware. For example, various general-purpose machines may beused with programs written in accordance with teachings of the presentinvention, or it may be more convenient to construct a specializedapparatus or system to perform the required methods and techniques.

[0102] The present invention also relates to computer readable mediathat include program instruction or program code for performing variouscomputer-implemented operations based on the methods and processes ofthe invention. The media and program instructions may be those speciallydesigned and constructed for the purposes of the invention, or they maybe of the kind well-known and available to those having skill in thecomputer software arts. Examples of program instructions include forexample micro-code, machine code, such as produced by a compiler, andfiles containing a high-level code that can be executed by the computerusing an interpreter.

[0103] Other embodiments of the invention will be apparent to thoseskilled in the art from consideration of the specification and practiceof the invention disclosed herein. It is intended that the specificationand examples be considered as exemplary only, with a true scope andspirit of the invention being indicated by the following claims.

[0104] The foregoing description of preferred embodiments of the presentinvention provides illustration and description, but is not intended tobe exhaustive or to limit the invention to the precise form disclosed.Modifications and variations are possible in light of the aboveteachings or may be acquired from practice of the invention. The scopeof the invention is defined by the claims and their equivalents.

What is claimed is:
 1. A method for processing signal strengthinformation from a radio frequency transmitter comprising the steps of:receiving signal strength information indicating a power for the radiofrequency transmitter at one or more first locations; receiving locationinformation representing a geographic location for one or more secondlocations; dividing the received signal strength information into one ormore subsets of signal strength information; determining, for each ofthe one or more subsets, a local mean such that the local meanrepresents an average for one of the one or more subsets; and estimatinga location for the local mean based on the received locationinformation.
 2. The method of claim 1 further comprising the step of:determining at least one distance between one or more estimatedlocations for one or more local means.
 3. The method of claim 2 furthercomprising the step of: dividing the received signal strengthinformation into one or more subsets based on the at least one distance.4. The method of claim 3, wherein said step of dividing furthercomprises the step of: determining the at least one distance based on aspeed of a receiver.
 5. The method of claim 4, further comprising thestep of: determining the at least one distance based on a speed of areceiver of the signal strength information.
 6. The method of claim 2,further comprising the step of: interpolating a local mean when the atleast one distance exceeds a predetermined distance.
 7. The method of 1,wherein said step of receiving location information further comprisesthe step of: receiving location information for one or more secondlocations including one or more of the following: a latitude, alongitude, and at least one of a plurality of first time stamps from areceiver of global positioning system information.
 8. The method ofclaim 7, wherein said step of receiving signal strength informationfurther comprises the step of: receiving said signal strengthinformation as a set of signal strength data based on a signal trace. 9.The method of claim 8, further comprising the step of: attaching atleast one of a plurality of second time stamps to the set of signalstrength data.
 10. The method of claim 9, further comprising the stepof: smoothing the plurality of second time stamps based on the pluralityof first time stamps.
 11. The method of claim 10, wherein said smoothingfurther comprises the step of: smoothing the plurality of second timestamps based on a slope for the plurality of first time stamps.
 12. Themethod of claim 1, wherein said step of determining further comprisesthe step of: determining a plurality of local means such that each localmean corresponds to one of the one or more subsets.
 13. The method ofclaim 12, wherein said step of determining further comprises the stepof: averaging one or more of the plurality of local means to provide awindow average.
 14. The method of claim 13, wherein said step ofaveraging further comprises the step of: determining a difference valuebased on one of the plurality of local means and the window average. 15.The method of claim 14, wherein said step of averaging further comprisesthe step of: determining a plurality of difference values.
 16. Themethod of claim 15, further comprising the step of: calculating astandard deviation based on the plurality of difference values.
 17. Themethod of claim 16, further comprising the step of: determining a signalcoverage at a location for a wireless device based on the followingequation:${{Cp}(r)} = {\frac{1}{2} - {{erf}\frac{w_{t} - {{LM}(r)}}{\sigma_{LM}}}}$

wherein r represents the location, σ_(LM) represents the standarddeviation, LM(r) represents the local mean corresponding to thelocation, w_(t) represents a service threshold for the wireless device,and erf is a normal distribution error function.
 18. The method of claim17, wherein said step of determining the signal coverage furthercomprises the step of: defining the location as at least one of the oneor more first locations.
 19. The method of claim 1, further comprisingthe step of: defining the one or more first locations as locations thatdiffer from the one or more second locations.
 20. A method fordetermining a signal coverage for a wireless device comprising the stepsof: receiving signal strength information for a signal; receivinglocation information representing a geographic location for one or morefirst locations; determining one or more local means based on thereceived signal strength information; estimating one or more secondlocations for the one or more local means based on the one or more firstlocations; transforming the one or more second locations into a route;and calculating the signal coverage for the route based on a signalcoverage for at least one of the one or more second locations.
 21. Themethod of claim 20, wherein said step of calculating further comprisesthe step of: calculating the signal coverage for the route based on thefollowing equation:$R_{cp} = \frac{\sum\limits_{k}{{{C_{p}(k)} \cdot \Delta}\quad (k)}}{\sum\limits_{k}{\Delta \quad (k)}}$

wherein C_(p)(k) is the signal coverage at the one or more secondlocations, and Δ(k) is the relative distance between two of the one ormore second locations.
 22. The method of claim 20, further comprisingthe step of: determining a standard deviation based on the receivedsignal strength information.
 23. The method of claim 22, wherein thestep of determining the standard deviation further comprises:determining the standard deviation based on one or more differencevalues, such that a difference value represents the difference between alocal mean and a corresponding window average.
 24. The method of claim20, wherein said step of receiving location information furthercomprises the step of: receiving the one or more first locationsincluding one or more of the following: a plurality of latitudes, aplurality of longitudes, and at least one of a plurality of time stampsfrom a receiver of global positioning system information.
 25. The methodof claim 24, wherein said step of transforming further comprises thestep of: determining the route based on the plurality of latitudes andthe plurality of longitudes; and dividing the route into at least twosegments based on the plurality of latitudes and the plurality oflongitudes when the at least two segments exceed a route break distance.26. The method of claim 25, wherein said step of determining the routefurther comprises the step of: transforming the plurality of latitudesand the plurality of longitudes into the route such that the routeincludes one or more directions and one or more distances arranged toform the route.
 27. The method of claim 22, wherein said step ofdetermining the signal coverage along the route further comprises thestep of: determining the signal coverage at one of the one or moresecond locations based on the following equation:${{Cp}(r)} = {\frac{1}{2} - {{erf}\frac{w_{t} - {{LM}(r)}}{\sigma_{LM}}}}$

wherein r represents one of the one or more second locations, σ_(LM)represents the standard deviation, LM(r) represents a local meancorresponding to one of the one or more second locations, w_(t)represents a service threshold for the wireless device, and erf is anormal distribution error function.
 28. A system for processing signalstrength information from a radio frequency transmitter comprising:means for receiving signal strength information indicating a power forthe radio frequency transmitter at one or more first locations; meansfor receiving location information representing a geographic locationfor one or more second locations; means for dividing the received signalstrength information into one or more subsets of signal strengthinformation; means for determining, for each of the one or more subsets,a local mean such that the local mean represents an average for one ofthe one or more subsets; and means for estimating a location for thelocal mean based on the received location information.
 29. The system ofclaim 28 further comprising: means for determining at least one distancebetween one or more estimated locations for one or more local means. 30.A system for determining a signal coverage for a wireless devicecomprising: means for receiving signal strength information for asignal; means for receiving location information representing ageographic location for one or more first locations; means fordetermining one or more local means based on the received signalstrength information; means for estimating one or more second locationsfor the one or more local means based on the one or more firstlocations; means for transforming the one or more second locations intoa route; and means for calculating the signal coverage for the routebased on a signal coverage for at least one of the one or more secondlocations.
 31. The system of claim 30, wherein said means forcalculating further comprises: means for calculating the signal coveragefor the route based on the following equation:$R_{cp} = \frac{\sum\limits_{k}{{C_{p}(k)} \cdot {\Delta (k)}}}{\sum\limits_{k}{\Delta (k)}}$

wherein C_(p)(k) is the signal coverage at the one or more secondlocations, and Δ(k) is the relative distance between two of the one ormore second locations.
 32. A system for processing signal strengthinformation from a radio frequency transmitter comprising: at least onememory comprising: code that receives signal strength informationindicating a power for the radio frequency transmitter at one or morefirst locations, code that receives location information representing ageographic location for one or more second locations, code that dividesthe received signal strength information into one or more subsets ofsignal strength information, and code that determines, for each of theone or more subsets, a local mean such that the local mean represents anaverage for one of the one or more subsets; and at least one processorthat executes said code.
 33. A system for determining a signal coveragefor a wireless device comprising: at least one memory comprising: codethat receives signal strength information for a signal, code thatreceives location information representing a geographic location for oneor more first locations, code that determines one or more local meansbased on the received signal strength information, code that estimatesone or more second locations for the one or more local means based onthe one or more first locations, code that transforms the one or moresecond locations into a route, and code that calculates the signalcoverage for the route based on a signal coverage for at least one ofthe one or more second locations; and at least one processor thatexecutes said code.